Hybrid DWT-SVD audio watermarking
Ahmad Mohammad2010, 2010 Fifth International Conference on Digital Information Management (ICDIM)
visibility
…
description
8 pages
link
1 file
Many effective watermarking algorithms have been proposed and implemented for digital images and digital video, however, few algorithms have been proposed for audio watermarking. This is due to the fact that, the human audio system is far more complex and sensitive than the human visual system. In this paper, we describe an imperceptible and robust audio watermarking algorithm based on the discrete wavelet transform. Performance of the algorithm has been evaluated extensively, and simulation results are presented to demonstrate the imperceptibility and robustness of the proposed algorithm.
Related papers
Improved Audio Watermarking Using DWT-SVD
2011
Digital audio watermarking involves the concealment of data within a discrete audio file. Applications for this technology are numerous. Intellectual property protection is currently the main driving force behind research in this area. In this paper we present an ef- ficient audio watermarking algorithm in the frequency domain by embedding an inaudible audio water mark. Comparison of two different algorithms i.e. Discrete Cosine Transform (DCT)-Singular Value Decomposition (SVD) and Discrete Wavelet Transform (DWT)-SVD is presented here. The effectiveness of these algorithms is verified by conducting experimentation. Experimental results show that the wa- termarked audio has good imperceptibility and is robust against different kinds of attacks, such as noise adding, re-sampling, cropping.
An Effective Audio Watermarking using DWT-SVD
Audio watermarking has been proved as a powerful tool against illegal manipulation of audio products. It is generally used as a multimedia copyright protection tool. In this paper, we propose an audio watermarking algorithm based on two mathematical functions: Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD). These algorithms performance is validated in the presence of the standard watermarking attacks. A new audio signal framing, DWT matrix formation and embedding methods are proposed and successfully implemented to improve the quality of watermarked audio. Natural variability of speech features allows watermarking alterations to be imperceptible to the human observer. On the other hand, significance of these features makes the system robust to common signal processing operations.
A Robust Blind Audio Watermarking Scheme Based on DCT-DWT-SVD
Lecture Notes in Electrical Engineering, 2018
In this paper, Watermarking hybrid sound algorithm is presented to protect the copyright of audio files, which, in addition to the clarity and consistency of the audio signal, has increased the strength and strength. To this end, a hybrid algorithm for voice signal cryptography is presented in the three domain parser transforms, discrete cosine transform, and discrete wavelet transforms. So, after discrete cosine transformation (DCT) on the host signal, by selecting the sub-band of low frequency, which contains the highest signal energy, two discrete wavelet transform (DWT) with a random wavelet filter on the low-frequency coefficients of conversion A discrete cosine applies, after selecting the approximation coefficients, the resulting one-dimensional matrix is converted to a two-dimensional matrix, and finally the resulting matrix is applied to a single value decomposition (SVD), which results in the formation of a The diameter matrix is that the watermark bits are embedded in the first layer of the dipole matrix, so that the two bits with value S (1,1), S (2,2) of the matrix The diameter S is chosen, first compares the first and second intersections of the diameter matrix S, which is multiplied by the coefficient h multiplied by the obtained two bits and is used as a fixed value in the embedding formula and The title of the new watermark is embedded in S (1,1). The results of the implementation show that the proposed algorithm succeeded not only in achieving transparency and resistance to general audio processing attacks, such as Gaussian white noise, quantization rates, decreasing and increasing the rate of sampling, compression and low pass filtering. But has achieved better results than other similar algorithms.
Adaptive and Robust Audio watermarking in Wavelet Domain
Third International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP 2007), 2007
This paper presents a robust method of audio watermarking in the wavelet domain. In this method, the watermarked data is encrypted, then combined with a synchronization code and embedded in lowfrequency coefficients of wavelet transform. In this paper two techniques of quantization are employed for data embedding process. The magnitude of quantization step and embedding strength is adaptively determined according to the characteristics of the human auditory system (HAS). Therefore data embedding distortion is imperceptible for human ears. The experimental results show that the proposed watermarking scheme is transparence and very robust against common attacks such as additive Gaussian noise, low-pass filtering, resampling, requantization, shifting, cropping and MPEG compression.
Audio Watermarking Based on 3-level DWT
By evolution in computer and telecommunication, all kind of data is stored and distributed around the globe. However, transmission of this digital data is not much secured .An issue of copyright of data is always a major concern. Data hiding techniques can help preserving illegal distribution of digital data. In this paper we describe one of the vigorous data hiding technique known as digital audio watermarking, which embeds additional indistinguishable information in the audio signal by using discrete wavelet transform algorithm. The changes recorded by embedding and extracting the watermark are verified and displayed using signal to noise ratio as human auditory system(HAS) is far more complex than human visual system (HVS) so to determine noise introduced in watermark we will show result based on signal to noise ratio(SNR).
An effective Audio watermarking.pdf
International Journal of Computer Applications, 2013
Audio watermarking has been proved as a powerful tool against illegal manipulation of audio products. It is generally used as a multimedia copyright protection tool. In this paper, we propose an audio watermarking algorithm based on two mathematical functions: Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD). These algorithms performance is validated in the presence of the standard watermarking attacks. A new audio signal framing, DWT matrix formation and embedding methods are proposed and successfully implemented to improve the quality of watermarked audio. Natural variability of speech features allows watermarking alterations to be imperceptible to the human observer. On the other hand, significance of these features makes the system robust to common signal processing operations.
Audio Watermarking using DWT-SVD-BFO
The main aim of this work is to develop a new watermarking algorithm within an existing discrete wavelet Transform (DWT) and singular value decomposition (SVD) framework. This resulted in the development of a combination of DWT-SVD-BFO (bacterial foraging optimization) watermarking algorithm. In this new implementation, the embedding depth was generated dynamically thereby rendering it more difficult for an attacker to remove, and watermark information was embedded by manipulation of the spectral components in the spatial domain thereby reducing any audible distortion. Further improvements were attained when the embedding criteria was based on bin location comparison instead of magnitude, thereby rendering it more robust against those attacks that interfere with the spectral magnitudes. The further aim of this thesis is to analyze the algorithm from a different perspective.
Robust Audio Watermarking based on HWD and SVD
2012
To protect copyright of audio signals several watermarking algorithms have been proposed in recent years. Many of them are based on wavelet transform but these methods are not robust enough against signal processing attacks. This paper presents a new audio watermarking algorithm based on Hybrid wavelets and Directional Filter banks (HWD) and Singular Value Decomposition (SVD). The proposed method embeds the watermark in the directional subbands of audio matrix. To do multiple embedding, framing is used and each frame is split to two parts. The first one is used for the synchronization code and the other for watermark embedding. Synchronization code is embedded in time domain to achieve more efficiency and watermark is embedded in SVDblocks of different directions using HWD. Experimental results show that proposed method has increased robustness and imperceptibility. It also has an acceptable data payload.
Perceptual Audio Watermarking by Learning in Wavelet Domain
2006
Conventional blind watermark (WM) decoding schemes use correlation-based decision rules because of their simplicity. Drawback of the correlator decoders is their performance relies on the decision threshold. Existence of an undesirable correlation between the WM data embedded through a secret key and the host signal makes the decision threshold specification harder, especially in noisy channels. To overcome this drawback, we propose a SVM-based decoding scheme which is capable of learning the embedded WM data in wavelet domain. It is shown that both decoding and detection performance of the introduced WM extraction technique outperforms state-of-the-art correlation-based schemes. Test results demonstrate that learning in the wavelet domain improves robustness to attacks while reducing complexity
Implementation of Audio Watermarking Using Wavelet Families
The implementation of audio watermarking in images using wavelet families is proposed in this paper. The secret data used is audio and the input image is color image. The algorithm is based on decomposition of images using Haar wavelet basis, Daubechies wavelet, Biorthogonal wavelet, Reverse biorthogonal wavelet and Discrete approximation of Meyer wavelet. The later part of the paper compares the watermarking results of different wavelet families for quality metrics such as PSNR, MSE, RMSE and Entropy. The retrieval of secret data is satisfactory under certain attacks such as cropping, compression, noise effect, geometrical attacks and contrast enhancement.
The International Arab Journal of Information Technology, Vol. 8, No. 3, July 2011
& ! "
!
" # $
'
" # $
" %
" %
%
Many effective watermarking algorithms have been proposed and implemented for digital images and digital video,
however, few algorithms have been proposed for audio watermarking. This is due to the fact that, the human audio system is
far more complex and sensitive than the human visual system. In this paper, we describe an imperceptible and robust audio
watermarking algorithm based on the discrete wavelet transform. Performance of the algorithm has been evaluated
extensively, and simulation results are presented to demonstrate the imperceptibility and robustness of the proposed
algorithm.
Multimedia, copyright protection, audio watermarking, imperceptibility, robustness, transform(domain
watermarking, and discrete wavelet transform.
Received September 16, 2009; accepted January 3, 2010
'
" $ !
(
!
)
!
+ ,
$
( *
)!
"
)
)"
!
!! " )
, (
*
+
) )
"
)
!
! )
", '
$ +"
"
+"
! (
+
.
(
"
)
(
),
/
"
$
$
(
*
$ +
) )
)
012,
( $
!
!
!
"
) .
$
!
$ ! "
(
$ +
) )
!
(
*
032,
!
(
*
4!
)
!
+
!)
( ") 5
4!
4! "
4! 0
2, '
(
$
! )
4!
"$ "(
)
+!
)
) + " 6 ! + "7 4!
!
(
* , / ! + "
+
(
*
!
) !
! +
! 4! "
!
!
( "
(
*
* $
!
+
,
8 +!
(
*
$
,' (
*
!
!$$
!
* !
))
$
! +
)
+
(
! )
) +
,
(
4!
!
+!
( $
!+
(
*
4!
!
6
"
!
7
09 :2,
+
+
!
) $ ! +" $ (
0: ;2, / *
$
4!
<
!! "
$
*
<
!
, =
(
*
)
+
!
+"
!
)
$
)
!
(
) !
"
*
)
) + 0
92, /
!
(
*
$ "
"
)
4!
(
)!
!
( $
( *
)
* !
)
,
& 4! "
!
(
*
4!
) " !
)
)! ) )
4! "
*
!
!
" "
$ (
*
0 32, /
4!
)
) !
( "
"
(
*
,
)!
!
& !
'
6-&'7
'
6- '7
> $
'
6->'7, / 0 2
& !
!
$
4! "
,3 ? <
,3 ? <
)
(
(
* 4!
!
$ "
)
) *
!
? <,
$
!
$ "
$
)
)
"
*
+ "
)
$
+ !
)
$ !
0 2
(
*
)
+"
$ )
+ (
+ , '
) +
+
DWT–Based Audio Watermarking
(
(
:
*
+!
!
=
)
!
)
4!
+
(+
6
)
!
!
( *
+
)
!
)
.
+!
!
)
) )
/
(
'
*
->'
$
(
(
(
*
,
)!
$ "
,
( ) )
!
)
+
"
!
->',
!
!+ +
(
(
!+ +
+!
*+
+
) )
$ +
, /
*
) )
)
!
(
(
!
$ !
!
+!
*,
+
)) )
* + , /
+
!
)
) + "
,
(, /
(
"7 )
( $
,>
<
)
(
.
,/
(
!
)
! +
!
)
(
)
( $
$
!
+
) (
!
!
"
g0(n)
"
, /
!
+
(
)"
!
!
0 :2,
,' "
"
<
( $
!
(
$ "
* (
A
(
$
WL( n , j ) = ∑ WL( m , j − )h; ( m − n )
m
WH ( n , j ) = ∑ WL( m , j − )h ( m − n )
m
4!
!)
)
()
)
B
)
$ "
)
4!
$
()
jth
$
th
+
(j+1)
)
$ " !
(
$ ",
4!
+
!
+
(
0
*
@
4! "
<
+
"
(
*
+
->' +
!
!
!
2,
#
$
'
!
( ) )
> $
'
(
(
-
*
)
+
! ,
+
6->'7
*
+
(
)
!
(
)
%
+
)
5 (
"
*
, '
)) "
+
,
! 5
*
B
&
!
* )
)
)
->' +
)
!
+
)
->'
+
!
(
),
, .)
"
(
.(
Img = {Img( k,j),
<
$
*
M1 x M2,
(
0 ≤ k ≤ M1, 0 ≤ j ≤ M2}
(
"
)!
!
!
.
->'
$
( $
+
+
#
"
, '
)
!
!
!+ 4!
)
,
(
(
+
g1(n)
-!
) )
"
)
!
( $
+
4!
(
& !
jth
jth
"
$ (
!
nth
nth ( $
h1(n)
WL( n, j ) = ∑WL( k, j + )g;( n − k ) + ∑WH(l, j + )g ( n − l ) 6 7
k
l
'
)
> $
) $ !
WL(n,j)
WH(n,j)
h0(n)
)
) $ ",
4!
+
( $
, / )
"
(
,
/
( $
)
!
(
.)
!
'
(
.
+
+
!
!
) $
+
*
"
! +
+"
(
*
, &
"
)
(
)
+
) . "
<
$
!
!
"
)
(
)
+
)
!+ +
) )
! +
'
!
"
+
$
6
4!
*
)
! (
) )! , '
6
(
*7
!
7
)
4! " +
2, >
*
+ (
(
*
0 92 ! ) !
!
*
,
)
0@
(
"
W
. Img
M1 x M2,
W = {W 6i7 = Img (k,j),i = k x M + j 0 ≤ k ≤ M1, 0≤ j ≤ M2}
6 7
,C
<
6 7
Wni = Wi/255;
$
637
$
697
W +"
+" 99,
(M2 + 1) ≤ i ≤ ((M1 × M2) + M2)
6 7
@
,
The International Arab Journal of Information Technology, Vol. 8, No. 3, July 2011
)) "
(
$
->'
, ' ->' )
) !
!+ +
( + (
& !
(
A2
)) .
!+ +
D1
D2
$
$
!+ +
) $ ", /
)
(
)
(
$ ->'
$ +
!
->' $ ,
Wi = Wni . 255;
!
-
& !
3,
4!
( )
%'
'
(
* .
)
!
* $
>
$
, '
*
$
(
6>- 7
'
!
(
(
)
!
*
,
"
.
)
)
(
!
+
)
)) "
)
+
!
,
)!
,
+
(
*,
(
<
*, '
$
)
! ,
(B
$ ->'
(
*
)) .
(
(
(
* (
.
.
+
+
4!
(
*
*
!
*
)
+
!
(
$
!+
Wt
! B
Wti = WD i − D i 5 i = {1,120,240...L2} ,
(M2 + 1) ≤ j ≤ ((M1 × M2) + M2)
,-$
Wt +"
+
Wni = Wti/α ;
3,
(
*
<
(
)
*$
(M2 + 1) ≤ i ≤ ((M1 × M2) + M2)
! ) " Wn +" 99
"
(
!
*,
)
617
α
Wn,
!
!
) ) !
)
,
4!
+
;@ . 9:
( !
(
, '
<
*
,
& !
!
!
,'
(
*
> D
") ,
<
"
,
*(
& !
.
*,
!
$ !
*
( !
)
33, * <
6 - 4! "7, '
(
7
(
!
(
+
&
)
!
6
(
"
( !
(
.
*
(
)
)
")
$
+
(
*
,
W t i =Wn i ×α ; ( M2+1) ≤ i ≤ ( ( M1×M2 )+M2 ) 6@7
#
!
/
( D2i + W t j ) ; i = {1,12 0,240... L2} , and
( M2 +1 ) ≤ j ≤ ( ( M1× M2 ) +M2 )
6:7
WD2=
=
−
D
2
;
i
{
(
2
:
2
1
9
)
,
(
1
2
1
:
2
3
9
)
.
..
(
L
2
1
1
9
:
L
2
}
,
i
and ( M2+1 ) ≤ j ≤ ( ( M1×M2 )+M2 )
(
W + *
)
) )
$ ->' )
<
(
4!
! ) !
!+ +
@,
+"
!+ +
)
$
:
+
(
$
(
-
, =! )! !+ +
+
.)
9,
(M2 + 1) ≤ i ≤ ((M1× M2)+ M2)
+
)
"
*
,
!
(
*
" $ !
(
)
(
B )
) + " 6 ! + "7
+!
0 2, =
!
) "
)!
"!
)
$
))
,/ (
( ( )
)
!
) )
->' +
,
(
+
+
!
,
!
-
/ )
) + "
)
) ! 4! "
+
(
*
(
!
, /
!
4! "
)
$ +"
(
*
)
) +
,
'
!
)
) + " ( !
C
8
6 C87
+
$
!
!+
$
! ,
C
8
6 C87
(
!
!
!
+ (
!
!
(
*
!
,
'
C8
)!
4!
6 7 (
A
)
) )
A'
)
(
* ) )
,
6 ;7
SNRL(dB) = 10log 10
2
∑ n An
' 2
∑ n (A n − A n )
6 7
DWT–Based Audio Watermarking
!
!
!
C8
+"
1
)
( "
+
(
)
) + "
' +
!
*
$
./) 0
9
3
*
)
!
" "
, '
)!
!
E! "
+
(
0 2
E
)
'
! .)
+
))
' + ,
(
!
6
) "
E 7 032, /
+ (
6 = 7
;,1@,
E
(
=
(
=
,
+
/ )
) +
) + +!
"
"
"
D "
"
)) "
4!
(
*
!
+ (
& !
$ !
(
' +
+$ !
& ! ,
"
) )
+
3 (
, '
"+ (
) !
!
,
'
!
,
) !
,'
'
+, >
*
!
,
) !
& !
,
'
,'
) )
,
'
+, >
*
& !
) )
3,
,
C8
( $
(
C8
$ !
;
The International Arab Journal of Information Technology, Vol. 8, No. 3, July 2011
(
" )
!+
$
(
*
,
( )
)
(
(
*
) (
"
+
+ (
(
, '
)
;
"
) ,'
$
/ )
!
) +
<
' +
"
! 6 C8
' + ,
, / )
) +
+
=
" 6 C8
& +
(
+"
(
*
+
* 0 ;2,
* (
)
+ F
!
F
(
(
) )!
)
!
) !
0 2, '
.
(
*
)) "
*
(
& !
9G
!
) ) !
) $ ", '
!
)
*
(
*
$ "
( $
( )
+
.
+
(
*
*,
=
!+
$ $ !
6 )
7
.
(
* (
!
"
+ (
(
*
(
*
.
* (
*
!
ρ (
)!
(
4!
+ (,
$
(
*
!
$ ) )
$
)
) ,
7
= 7$ ! ,
)1*
@,99 9
9,; 3
!
(
!
./)
9,;;
9,;;
*F
*
>
*
!
)
"
4!
(
$ !
)
!
!
"
" !
)
)
)
*
"
)
"
+
+!
,
ρ( w , ŵ ) =
!
"
(
) )
*
*
,
$
"
!)
,
(
wH
'
(
)
+ (
"
! +
).
$ ", '
; 6
)7,
6ρ I ;,1 17
.
6ρ I ;,1: 7
.
6ρ I ;,1: 7
9, .
(
*
$
!
*
(
* w
(
"
6)
ρ
)7
C
;
6ρ I ;,1 @7
) "
6ρ I ;,1 97
6 7
.
$ +
!
6ρ I ;,1 7
& !
N
N
∑ w ŵ
i= i i
N
N
∑ wi ∑ ŵi
i=
i=
*
6ρ I ;,1 7
6ρ I ;,19;7
J
6ρ I ;,1:;7
*
(
*
!
,
*
* $ !
DWT–Based Audio Watermarking
!
6ρ I ;,1337
C
;
6ρ I ;,1 @7
) "
6ρ I ;,@ 97
6ρ I ;,1 ;7
.
6ρ I ;,: 7
*
6ρ I ;,; 7
6ρ I ;,13;7
.
6ρ I ;,@:;7
& !
, .
(
*
$
!
2
J
6ρ I ;,; ;7
*
*
(
3 4
"
!
(
*
$
+
)
+ !
)
)!+ ,
( $
"
!
$ !
(
)
)
) + " 6 C8
= 7
+!
6
*
*
7
(
$
) ) ,C
*
)
( )
' +
C8
=
!
(
4!
"(
)
0 12,
)
! (
' +
(
!
) )
)
+
4! ,
$
!
!
!
)
!
(
*
4!
+"
/
&
) / ! " 0 2,
$
' +
,
4! ,
)
(
C8
* "
#!
=
!
0 32
-
, 3
0:2
,3:
0:2
, ;
./)
. 0@2
(
0 12
)
& 4!
)
"
!
*
, 9
0 2
, ;
,33
:,1
3,1;
@,91
3,3
,@:
* +
!
$
)"
) ! ,
"
*
4!
$ +
+
$
( $
!
!
!
)
!
,/
) ) ( ) )
!
(
*
( $
,
'
!
(
)
)) )
+
)
) +"
+! ", /
!
! + "
) )
!
(
*
!
* "
0 2
0:2
!
$
,
$ !
)1*
$
$
(
!
+!
,
) )
!
!
(
*
+
$
+"
)
) +
)
!
(
) )
) $
+
)
*
0 2
,1
032
$
, Digital Watermarking for Audio
Data in Techniques and Applications of Digital
Watermarking and Content Protection
! #
;; ,
-= F
!
)BKK(((, + ,
K
) ! K !
K ;;1,
, L !
>
* B & !
))
M in Processings of
the IEEE International Conference on
Multimedia and Expo )), ;
;
;;;,
, >
!
,
! *
,
L'
4!
))
>
*
M Artech
The International Arab Journal of Information Technology, Vol. 8, No. 3, July 2011
092
0 2
0:2
0@2
012
0 ;2
0
2
0
2
0
2
0 32
0 92
0
2
0 :2
0 @2
House, Psychoacoustics: Facts and models
)
D
;; ,
,
/, L8 +!
!
>
*
'
M IEEE
Transactions on Multimedia $ ,
,
)),
3
;; ,
%,
* %, L
)!
!
E! "
!
"
!
! 8 )
M Journal
of the Audio Engineering Society $ , 3;
,
)), 1 1:@ 11 ,
>, N ! -,
C,
! ,
L'
4!
M IBM System
Journal $ , 9 )),
11 ,
. /, ?
%,
',
',
L !
)
) !
>
*
!
M IEEE Transactions on Image
Processing $ ,
,
)), :
@:, 11:,
. /,
,
%, L>
*
M
#
;; ,
$
C,
))O
', L/
) "
!
) "M
in Proceedings of the IEEE International
Workshop on Multimedia Signal Processing )),
@ ;; ,
+ ,
* , L !
>
*
+
"
(
& 4! "
)
(
" /
M
Digital Signal Processing $ , 1
,
)),
9 :: ;;1,
N ! -, ! ,
>, L
M
in Proceedings of the International Conference
on Info Hiding )), 19 9 11 ,
/& /
6/
&
)
/ ! "7
)BKK((( ) ,
;;1,
? < +
,
&, L/
'
4!
) "
>
*
M
!
#
;;;,
?
,
P, L C $
(
+ *(
& (
?
M
/
'
!
"
D
'
"5 $ ,
, @ )), @@9 @@1
;; ,
* ,
8,
? *
, 8 +!
L !
>
*
#
& 4! "
$
)
) ! M IET Information
Security $ ,
, 3 )), 1 9; ;;@,
, L '
"
! 8
!
)
B '
> $
8 )
M
IEEE Transactions on Pattern Analysis and
Machine Intelligence $ ,
, : )), :3 1
1@1,
=<
,
*! ,
C, L
D!
>
*
'
4! M in
Proceedings of the Multimedia and Security
Workshop C ( P * )), 9 9
;;9,
0 12
0 ;2
0
2
0
2
0
2
0 32
0 92
, N!
&,
/* < !
,
L
$ !
!
>
*
'
4! '
& 4! "
) !
M in
Proceedings of the International Conference on
Advances in Information Systems )), 3 ; 33;
;;9,
+
,
&, 8 " &, %, &
et al L
*
*B !
>
*
* M in Proceedings of the
International Conference on Information
Technology: Coding and Computing )), 31 93
;; ,
(
, J ! ,
' ( * ,
" ,
L8 +!
!
>
*
#
)!
*
M Signal Processing $ ,
, )),
: 99 11@,
' * %,
. , L
! #
"
!
*
M in
Proceedings of the 7th International Conference
on Signal Processing Applications and
Technology )), 3: 3@; 11 ,
' * %,
. , L
!.
"
!
#
"
!
*
M in Proceedings
of IEEE Southeastern )),
11:,
#!
#,
, !
>
*
#
$
Project Report
<
# $
"
$ +
)BKK+! , ,+ ! , !, KQ )
K)!+
K
! R(
* K!!R R ! R( ;; ,)
;; ,
P
/,
?
, L
( *
B
C $
!
>
*
M IEEE Transactions on Speech and
Audio Processing $ ,
, 3 )), @ @
;; ,
!
! $
!$5 6
"
# $
" %
$
P
'
1@@
)!
11 ,
'8
+
!*
1@9
# $
= * # $
" % )
" % )
( *
$
'
!
8
?"
% )
!
119,
! " # $
" %
= +
119
(
(
)
,
)!+
) )
(
)!
$
D /
)
!
( *
!
(
* ,
DWT–Based Audio Watermarking
$
.
# $
"
1@
*
)
;;;,
"
)
")
-
# $
" #
11
) $ ",
- )
! " # $
" %
!
!
$
)!
# $
"
%
!
"
> +
/ , %
,
1@1
+
)!
",
7
;;:,
$
)
Related papers
Como Formular um Problema de Pesquisa?
Manuscript, 2024
Food Defnse, Food Safety and Food Industry
Lucrări ştiinţifice - Universitatea de Ştiinţe Agricole şi de Medicină Veterinară "Ion Ionescu de la Brad" Iaşi. Seria medicină veterinară, 2023
Mikołaj Jarmakowski, Arkońska wróżba z kołaczem. Gest zasłonięcia się w kulturze duchowej Słowian w świetle analizy antropologicznej.
Argumenta Historica, nr 10, red. Anna Paner, s. 39-48, 2023
AMADAS Y ¿CHOCANTES? NOTAS SOBRE LA REPRODUCCIÓN, VENTA Y CIRCULACIÓN DE ESTAMPAS Y RETRATOS DE FERNANDO VII (NUEVA ESPAÑA, 1808-1809)
Historia Mexicana, 2024
Questioning medicine’s discipline: The arts of emotions in undergraduate medical education
Emotion, Space and Society, 2013
New Evidence for the 10th Century BCE at Tel Gezer
Jerusalem Journal of Archaeology, 2021
Maaß - Borghardt - Der Wert der Preise
Der Wert der Preise. Valorisierungsdynamik in der deutschen Literaturpreislandschaft 1990-2019, 2022
Ripensare l’educazione al progetto, in caso di emergenza
Actuar en la emergencia. La agencia del diseño durante (y después) de la covid-19, 2003
NOVEL ARCHAEOMETRICAL AND HISTORICAL TRANSDISCIPLINARY INVESTIGATION OF EARLY 19th CENTURY HELLENIC MANUSCRIPT REGARDING INITIATION TO SECRET "PHILIKE HETAIREIA
Zenodo (CERN European Organization for Nuclear Research), 2023
Multisystem Inflammatory Syndrome in Children (MIS-C) Associated with SARS-CoV-2 Infection: A Single Center Experience
The Central European Journal of Paediatrics, 2021
Frequency of Streptococcus mutants in patients having dental caries; a data from clinical setting in rural area of Balochistan
World Journal of Biology and Biotechnology, 2021
Molecular epidemiology of HBV, HCV and HDV in general population of Afghanistan
conferenceseries.com, 2017
Protein function in the crystalline state
Acta Crystallographica Section A Foundations of Crystallography, 2004
On the classical equivalence of monodromy matrices in squashed sigma model
Journal of High Energy Physics, 2012
Strategi Marketing Public Relations untuk Membangun Citra Innisfree melalui Penggunaan Virtual Reality
Jurnal Penelitian Komunikasi, 2019
Changes in volatile compounds of human urine as it ages: Their interaction with water
Journal of Chromatography B, 2013